1. Field of the Invention
The present invention relates to an ultrasonic image analyzing apparatus and, more specifically, to an ultrasonic image analyzing apparatus which performs, on the basis of observation image information in an ultrasonic diagnosis system, image analysis of a body portion being observed.
2. Related Background Art
As is well known, an ultrasonic diagnosis system is adapted to determine, on the basis of ultrasonic tomographic image information on a portion being inspected (such as an affected portion of the body), the properties of the tissues of the inspected portion, and to display a lesion portion caused by cancer or the like as a color image on a screen, etc, so as to allow a diagnosis. Also, a great number of proposals have been made concerning diagnosis methods which can be carried out by such a system.
U.S. Pat. No. 4,855,911 describes art entitled "ULTRASONIC TISSUE CHARACTERIZATION", which relates to the following diagnosis method: in an ultrasonic diagnosis system, a scatterer number density (SND) is calculated by obtaining a sum of scatter components from a tissue, and compared with predetermined parameters, thereby determining the properties of the tissue.
U.S. Pat. No. 4,817,015 describes art entitled "HIGH SPEED TEXTURE DISCRIMINATOR FOR ULTRASONIC IMAGING", which relates to the following ultrasonic tissue-property diagnosis method: first, a region of interest (hereinafter abbreviated to "ROI") is set in a portion being inspected, and then, an abnormality of the properties of the tissues is determined on the basis of two of the four parameters consisting of a value b indicating the square of the mean of intensities of the echos reflected from the ROI, a value t indicating a sum of a total average of the backscatter, a noise power spectrum d bar, and an integrated value p of the difference obtained by subtracting a Gaussian noise component from the noise power spectrum d bar.
In recent years, however, while computer image processing has advanced, various efforts have been made, in ultrasonic diagnosis systems, to apply texture analysis to quantitative diagnosis employing endoscopic ultrasonography (hereinafter abbreviated to "EUS") with a view to improving the reliability of the results of diagnosis. For example, an example of such analysis is published in the following Japanese document: "Quantitative Diagnosis Employing Texture Analysis over Ultrasonic-Endoscopic Image (First Report)" (GASTRORENTEROL. ENDOSC. 32:1363-1368, 1990). The above-mentioned EUS is an apparatus which performs scanning of, for example, the inside of an alimentary canal by an ultrasonic probe comprising an ultrasonic vibrator so that an ultrasonic image is obtained to allow diagnosis of an affected portion. An example of a conventional ultrasonic diagnosis system employing such texture analysis will be described with reference to FIG. 15 et seq.
As shown in FIG. 15 (a structural block diagram), an ultrasonic observation apparatus 1, including an ultrasonic scope having an ultrasonic probe, observes a portion being inspected with an ultrasonic wave, and obtains a tomographic image of the inspected portion, which image is displayed on a display 2 consisting of a Tv monitor. A signal outputted from the ultrasonic observation apparatus 1 to the display 2 (alternatively, a signal outputted from a VTR, not shown) is also inputted to an image processing unit 3. The inputted signal is converted into a digital signal by an A/D converter 4, and written into a frame memory 5. The frame memory 5 has, as shown in FIG. 16, a multiplicity of pixels, for example 640.times.512 pixels, within which a ROI 5A is set, the ROI consisting of, for example, 9.times.9 pixels, as shown in FIG. 17. A signal from the ROI 5A is inputted to a characteristic amount calculating section 6, which section 6 calculates characteristic amounts of the image.
Said texture analysis is used as a means for calculating such characteristic amounts. Texture analysis per se is already known, as described in, for instance, "Fundamentals of Image Recognition (II)" (a Japanese Document published by Ohm-sha, pages 195 to 200), and includes methods such as a method employing density co-occurrence matrices, a density level difference method, and a density level run-length method and a power spectrum method.
The texture analysis method employing density co-occurrence matrices is fundamentally based on the evaluation of a two-dimensional combined probability density function f (i, j.vertline.d, .theta.). The function f (i, j.vertline.d, .theta.) is a probability density function indicating the probability that a pixel which is away from another pixel having a density value i by a distance d in the direction .theta., has a density value j. Thus, density co-occurrence matrices express f (i, j.vertline.d, .theta.) with respect to each (d, .theta.) in the form of matrices, and i and j respectively indicate the position of a row and the position of a column. Normally, parameters expressed by the following formulae (1) to (5) are used as effective characteristic amounts: ##EQU1## In the above formulae, S.theta.(i, j.vertline.d) represents an element in the row i and in the column j of a matrix S.theta.(d), and NG represents the number of density levels of the image. The density averages Vx and Vy, as well as the fractions .sigma.x and .sigma.y are expressed by the following formulas (6a) to (6d): ##EQU2##
The density level run-length method is a method which may be effectively used when the relevant object is of a certain kind, such as a stripe pattern, whose image can be effectively analyzed by run-length coding. A density level run is a set of pixels which are linearly adjacent to each other and which have the same density value, and its length is the number of pixels contained in the density level run. If a calculation is made as to how many times a run having a density value i and a length j occurs in the .theta. direction of the image being processed, and if it is assumed that a density level run matrix R (.theta.) is a matrix expressing the results of the calculation with respect to each direction .theta., the density level run matrix R (.theta.) is expressed by the following formula where r (i, j.vertline..theta.) is a matrix element: EQU R (.theta.)=[r (i, j.vertline..theta.)]
Using the above R (.theta.), the following characteristic amounts are defined as parameters: ##EQU3## where NG represents the number of the density levels, NR represents the number of run lengths in the matrix R(.theta.), TR represents the total number of runs in the direction .theta. counted regardless of the length and density value, and TP represents the total number of pixels of the image.
The above description is that of texture analysis. Referring to FIG. 15, the values calculated using the above parameters are compared by a determination section 8 with threshold values .alpha. and .beta. set in a control section 7 of the processing unit 3 through a keyboard 9 or a track ball 10. If the calculated values are between the threshold values .alpha. and .beta., a display control section 11 operates for the color display of an image portion corresponding to the ROI 5A so that the values are converted by a D/A converter 12, mixed with a synchronizing (hereinafter abbreviated to "SYNC") signal from a TV SYNC signal generating section 13 by a mixer 14, and displayed on a TV monitor 15. The ROI 5A is moved in up-down and light-right directions to process the whole image. The region to be processed can be set through the keyboard 9 or the track ball 10. When the inside of the body cavity is to be observed by employing the ultrasonic scope, a body mark, consisting of an image illustrating the stomach, the duodenum, the great intestine or the like is simultaneously displayed on the TV monitor screen so that the position of observation is indicated.
Before such image analysis is performed by an ultrasonic image analyzing apparatus, the observer observes a tomographic image of a portion (the object of observation) on the monitor 2. At this time, the observer manually adjusts the density, the sharpness and the luminance of the image so as to facilitate observation by eye. The adjustment has hitherto been effected by an adjusting circuit accommodated in the ultrasonic observation apparatus 1 for adjusting the gain, the contrast and the sensitivity time control (hereinafter abbreviated to "STC") of the output to be transmitted and received from the endoscope.
Also, in the conventional image analyzing apparatus, when calculating the parameters for each ROI set on data on the relevant image, certain fixed size and certain fixed shape of the ROIs are used. Further, the position of ROIs is, at the time of the calculation, scanned by performing scanning in the horizontal and vertical directions on a plane of the image. Furthermore, the parameters are not particularly changed in correspondence with differences in the position of the ROIs.
In the conventional image processor having the above-described function, the parameters for the image analysis have been hitherto set by the operator. That is, it is necessary that parameters for use in calculating characteristic amounts in image analysis be suitably changed in accordance with the object organ or an object body portion being inspected, or the measurement conditions under which the observation apparatus performs observation (such as the type of the ultrasonic probe and the scanning method). Thus, the conventional apparatus has a drawback in that it is difficult to suitably set the parameters if the operator does not have sufficient experience and technical sense.
On the other hand, in the conventional ultrasonic observation apparatus employing the ultrasonic probe, if the probe is, for instance, a mecha-radial scanning type ultrasonic probe 16, such as that shown in FIG. 18, the ultrasonic probe 16 is rotated about a central point O, and the rotation allows tomographic image data in the directions Z in which the ultrasonic wave propagates to be obtained. The ultrasonic probe 16 is secured to the forward end of a flexible shaft 17. If the probe is of an electronic-radial scanning type, vibrator elements are arranged in a circular shape at a forward end, and the vibrator elements to be operated are electrically switched so that, similarly to the case of the mecha-radial type, image data indicating the conditions of the observation-object portion in the ultrasonic-wave propagation directions Z is obtained.
When topological image is obtained by the observation apparatus, the detection width increases with increases in the distance from the ultrasonic probe 16 to the portion being observed (i.e., as the observation-object position becomes relatively farther from the probe to the periphery thereof), thereby causing a reduction in resolution. In addition, as shown in FIG. 19, the beam diameter B has a certain relationship with the distance in each ultrasonic-wave propagation direction Z such that the beam diameter B increases with increases in the distance (i.e., increases at positions away from the position of the probe 16). This also causes the resolution to be lower at peripheral positions than at central positions. Also, the output .vertline.P (f).vertline. influenced by the spatial frequency characteristics of the ultrasonic probe 16 is such that, if the position of detection is close, a good characteristic is exhibited in a relatively wide range with respect to the reference frequency F.sub.0, as shown in FIG. 20, whereas if the position of detection is distant, great attenuation occurs in a high-frequency range, as shown in FIG. 21. Accordingly, it can be said that there is another risk of the resolution at peripheral positions being lowered.
In view of these risks, the conventional system has other drawbacks. As explained before, when calculating the parameters, the size and the shape of each ROI are fixed, and the position of ROIs is scanned by performing scanning in the horizontal and vertical directions on an image plane. This results in image data, varying in resolution, being subjected to the same processing. As a result, the calculation inevitably involves unnecessary calculating operations, thereby rendering the system disadvantageous in terms of time and level of precision. Furthermore, since the resolution is high at positions close to the ultrasonic probe 16, the probe 16 is usually brought into a position close to the portion to be observed. However, the conventional system performs the same processing regardless of the distance from the probe, thus failing to be favorable in terms of the level of precision.
When determining the structure of the tissues of the portion being observed, those calculated values of parameters, among calculated values of parameters such as the above-described short run emphasis and the long run emphasis, which lie between predetermined threshold values are used as characteristic amounts, and the tissue structure is determined from a combination of the parameters. However, in the conventional system, no consideration is given to the contribution ratio of parameters with respect to the calculation threshold values therefor, the combinations thereof and the determination based thereon, nor is consideration given to using calculation formulae including information on how far the object portion is from the ultrasonic probe 16. As a result, it has been difficult to realize correct determination and appropriate processing with respect to all of the regions of image data having different levels of resolution.
Before image analysis processing takes place in the conventional image analyzing apparatus, the gain, contrast and STC of the output to be transmitted and received from the endoscope is, as described before, adjusted by the observer (who specifies the density, etc. of the image) through the adjusting circuit provided within the observation apparatus 1. However, since this image adjustment is liable to be influenced by perception of individual operators, the condition created by the image adjustment cannot always be optimal to the image processing, such as texture analysis, which follows the adjustment.